A Capacity-Approaching Algorithm for Resource Allocation in MIMO-OFDM Multiple-Access Channel

This paper proposes a resource-allocation technique for Gaussian multiple-input multiple-output, orthogonal- frequency-division-multiplexing (MIMO-OFDM) multiple-access channel (MAC). Zero-forcing generalized decision-feedback equalizers (ZF-GDFE) are employed at the receiver to cancel completely the interferences produced by all the other users, while a novel matrix decomposition method based on the generalized channel singular-value-decomposition (SVD) is used to find the precoding matrices at each user´s transmitter. The achievable rate region is obtained by solving a series of weighted sum-rate maximization problems, and the associated users´ power distributions are efficiently found by a Lagrange dual- decomposition method along with a per-tone-based exhaustive search of decoding orders among users. The complexity can be further reduced by replacing the exhaustive search with a greedy algorithm. Simulation results show that the achievable rate region obtained by the greedy algorithm is very close to that achieved by the exhaustive search. Therefore, with a significant computational complexity reduction over the canonical minimum-mean- squared-error (MMSE) -based GDFE, the proposed algorithm provides an ideal scheme for practical systems such as uplink wireless MIMO-OFDM systems and upstream vectored digital subscriber lines (DSL).